title: Efficient L1 regularization-based reconstruction for fluorescent molecular tomography using restarted nonlinear conjugate gradient.
abstract: For the ill-posed fluorescent molecular tomography (FMT) inverse problem, the L1 regularization can protect the high-frequency information like edges while effectively reduce the image noise. However, the state-of-the-art L1 regularization-based algorithms for FMT reconstruction are expensive in memory, especially for large-scale problems. An efficient L1 regularization-based reconstruction algorithm based on nonlinear conjugate gradient with restarted strategy is proposed to increase the computational speed with low memory consumption. The reconstruction results from phantom experiments demonstrate that the proposed algorithm can obtain high spatial resolution and high signal-to-noise ratio, as well as high localization accuracy for fluorescence targets.
authors.forename: Junwei
authors.initials: J
authors.lastname: Shi
authors.forename: Bin
authors.initials: B
authors.lastname: Zhang
authors.forename: Fei
authors.initials: F
authors.lastname: Liu
authors.forename: Jianwen
authors.initials: J
authors.lastname: Luo
authors.forename: Jing
authors.initials: J
authors.lastname: Bai
mesh_terms: D000465:Algorithms; D005453:Fluorescence; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D017711:Nonlinear Dynamics; D019047:Phantoms, Imaging; D013997:Time Factors; D014054:Tomography / Q000379:methods*